docstr: Tests whether pad_and_concatenate works with scalars.
docstr_tok: ["Tests","whether","pad_and_concatenate","works","with","scalars","."]
code: def test_pad_and_concatenate_with_1d(self):
      """Tests whether pad_and_concatenate works with scalars."""
      array1 = 1.0
      array2 = 2.0
      result = numpy_pad_and_concatenate(array1, array2)
      self.assertTrue(np.array_equal(np.array([1.0, 2.0]), result))
  
      tensor1 = torch.tensor(1.0)
      tensor2 = torch.tensor(2.0)
      result = torch_pad_and_concatenate(tensor1, tensor2)
      self.assertTrue(torch.equal(result, torch.Tensor([1.0, 2.0])))
  
imports: import copy
  import unittest
  import numpy
  from transformers.data.data_collator import default_data_collator
  from transformers.testing_utils import require_accelerate, require_torch
  from transformers.trainer_utils import RemoveColumnsCollator, find_executable_batch_size
  from transformers.utils import is_torch_available
label_desc: Use image node_id 19 for calling the TrainerUtilsTest obj's underlying member method code with example usage: obj.test_pad_and_concatenate_with_1d() without return types